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Exact(9)
Let v(s) denote the maximum expected total reward, given the initial state s.
The objective is to determine (V^), the maximum expected total discounted reward vector over an infinite horizon.
where υ(s) denotes the maximum expected total reward, given the initial state s, and s ′ represents next state.
The solutions of the optimality equation correspond to the maximum expected total reward υ(s) and the SMDP optimal policy δ∗.
The solutions of the optimality equations correspond to the maximum expected total reward v(s) and the MDP optimal policy δ∗(s).
The solutions to the optimization problem correspond to the maximum expected total reward ζ(c) and the SMDP optimal policy δ∗.
Similar(51)
Their model minimizes the expected total cost including maximum tardiness cost among all parts, the cost of sub-contracting for exceptional elements, and the cost of resource underutilization.
Two related optimization models are then presented and solved to find the optimal results under uncertainty: Model 1 is expected total cost minimization, and Model 2 is maximum regret minimization.
Thus, a more feasible design might be to have the interim analysis at 2.6 years since the expected total study length for this design is close to optimal and the maximum duration of accrual and the maximum study length are smaller than those for the overall optimal design.
In particular, if no bound is imposed on negative prizes, the expected total effort can be arbitrarily close to the highest possible effort inducible when all contestants have the maximum ability with certainty.
TC expected total cost.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com